Is the immediate effect of marathon running on novice runners' knee joints sustained within 6 months after the run? A follow-up 3.0 T MRI study.

OBJECTIVE: To evaluate changes in the knee joints of asymptomatic first-time marathon runners, using 3.0 T MRI, 6 months after finishing marathon training and run. MATERIALS AND METHODS: Six months after their participation in a baseline study regarding their knee joints, 44 asymptomatic novice marathoners (17 males, 27 females, mean age 46 years old) agreed to participate in a repeat MRI investigation: 37 completed both a standardized 4-month-long training programme and the marathon (marathon runners); and 7 dropped out during training (pre-race dropouts). The participants already underwent bilateral 3.0 T MRIs: 6 months before and 2 weeks after their first marathon, the London Marathon 2017. This study was a follow-up assessment of their knee joints. Each knee structure was assessed using validated scoring/grading systems at all time points. RESULTS: Two weeks after the marathon, 3 pre-marathon bone marrow lesions and 2 cartilage lesions showed decrease in radiological score on MRI, and the improvement was sustained at the 6-month follow-up. New improvements were observed on MRI at follow-up: 5 pre-existing bone marrow lesions and 3 cartilage lesions that remained unchanged immediately after the marathon reduced in their extent 6 months later. No further lesions appeared at follow-up, and the 2-week post-marathon lesions showed signs of reversibility: 10 of 18 bone marrow oedema-like signals and 3 of 21 cartilage lesions decreased on MRI. CONCLUSION: The knees of novice runners achieved sustained improvement, for at least 6 months post-marathon, in the condition of their bone marrow and articular cartilage

Prevalence of abnormal findings in 230 knees of asymptomatic adults using 3.0 T MRI.

OBJECTIVE: To identify abnormalities in asymptomatic sedentary individuals using 3.0 Tesla high-resolution MRI. MATERIALS AND METHODS: The cohort comprised of 230 knees of 115 uninjured sedentary adults (51 males, 64 females; median age: 44 years). All participants had bilateral knee 3.0 T MRIs. Two senior musculoskeletal radiologists graded all intraarticular knee structures using validated scoring systems. Participants completed Knee Injury and Osteoarthritis Outcome Score questionnaires at the time of the MRI scan. RESULTS: MRI showed abnormalities in the majority (97%) of knees. Thirty percent knees had meniscal tears: horizontal (23%), complex (3%), vertical (2%), radial (2%) and bucket handle (1%). Cartilage and bone marrow abnormalities were prevalent at the patellofemoral joint (57% knees and 48% knees, respectively). Moderate and severe cartilage lesions were common, in 19% and 31% knees, respectively, while moderate and severe bone marrow oedema in 19% and 31% knees, respectively. Moderate-intensity lesion in tendons was found in 21% knees and high-grade tendonitis in 6% knees-the patellar (11% and 2%, respectively) and quadriceps (7% and 2%, respectively) tendons being most affected. Three percent partial ligamentous ruptures were found, especially of the anterior cruciate ligament (2%). CONCLUSION: Nearly all knees of asymptomatic adults showed abnormalities in at least one knee structure on MRI. Meniscal tears, cartilage and bone marrow lesions of the patellofemoral joint were the most common pathological findings. Bucket handle and complex meniscal tears were reported for the first time in asymptomatic knees

Use of artificial intelligence to automatically predict the optimal patient-specific inversion time for late gadolinium enhancement imaging. Tool development and clinical validation

Introduction With the worldwide diffusion of cardiac magnetic resonance (CMR), demand on image quality has grown. CMR late gadolinium enhancement (LGE) imaging provides critical diagnostic and prognostic information, and guides management. The identification of optimal Inversion Time (TI), a time-sensitive parameter closely linked to contrast kinetics, is pivotal for correct myocardium nulling. However, determining the optimal TI can be challenging in some diseases and for less experienced operators. Purpose To develop and test an artificial intelligence tool to automatically predict the personalised optimal TI in LGE imaging. Methods The tool, named THAITI, consists of a Random Forest regression model. It considers, as input parameters, patient-specific TI determinants (age, gender, weight, height, kidney function, heart rate) and CMR scan-specific TI determinants (B0, contrast type and dose, time elapsed from contrast injection). THAITI was trained on 219 patients (3585 images) with mixed conditions who underwent CMR (1.5T; Gadobutrol; averaged, MOCO, free-breathing true-FISP IR [1]) for clinical reasons. The dataset was split with a 90–10 policy: 90% of data for training, and 10% for testing. THAITI’s hyperparameters were optimised by embedding k-fold cross validation into an evolutionary computation algorithm, and the best performing model was finally evaluated on the test set. A graphical user interface was also developed. Clinical validation was performed on 55 consecutive patients, randomised to experimental (THAITI-set TI) vs control (operator-set TI) group. Image quality was assessed blindly by 2 independent experienced operators by a 4-points Likert scale, and by means of the contrast/enhancement ratio (CER) (i.e., signal intensity of enhanced/remote myocardium ratio). Results In the testing set, the TI predicted by THAITI differed from the ground truth by ≥ 5ms in 16% of cases. At clinical validation, myocardial nulling quality did not differ between the experimental vs the control group either by CER or visual assessment, with an overall "optimal" or "good" nulling in 96% vs 93%, respectively. Conclusions Using main determinants of contrast kinetics, THAITI efficiently predicted the optimal TI for CMR-LGE imaging. The tool works as a stand-alone on laptops/mobile devices, not requiring adjunctive scanner technology and thus has great potential for diffusion, including in small or recently opened CMR services, and in low-resource settings. Additional development is ongoing to increase generalisability (multi-vendor, multi-sequence, multi-contrast) and to test its potential to further improve CMR-LGE image quality and reduce the need for repeated imaging for inexperienced operators. Figure 1. Top: THAITI interface. Bottom: examples of experimental group CMR-LGE imaging. Table 1. Control vs experimental group. Data expressed as absolute number (%), mean ± SD, median [IQR]. ⧧ T-test; * Chi-square

Can marathon running improve knee damage of middle-aged adults? A prospective cohort study

Objectives To evaluate the short-term impact of longdistance running on knee joints using MRI. Methods 82 healthy adults participating in their first marathon underwent 3T (Tesla) MRI of both knees 6 months before and half a month after the marathon: 71 completed both the 4 month-long standardised training programme and the marathon; and 11 dropped-out during training and did not run the marathon. Two senior musculoskeletal radiologists graded the internal knee structures using validated scoring systems. Participants completed Knee Injury and Osteoarthritis Outcome Score questionnaires at each visit for self-reporting knee function. Results Premarathon and pretraining MRI showed signs of damage, without symptoms, to several knee structures in the majority of the 82 middle-aged volunteers. However, after the marathon, MRI showed a reduction in the radiological score of damage in: subchondral bone marrow oedema in the condyles of the tibia (p=0.011) and femur (p=0.082). MRI did also show an increase in radiological scores to the following structures: cartilage of the lateral patella (p=0.0005); semimembranosus tendon (p=0.016); iliotibial band (p<0.0001) and the prepatellar bursa (p=0.016). Conclusion Improvement to damaged subchondral bone of the tibial and femoral condyles was found following the marathon in novice runners, as well as worsening of the patella cartilage although asymptomatic. This is the most robust evidence to link marathon running with knee joint health and provides important information for those seeking to understand the link between long distance running and osteoarthritis of the main weight-bearing areas of the knee

Measurement of T1 Mapping in Patients With Cardiac Devices: Off-Resonance Error Extends Beyond Visual Artifact but Can Be Quantified and Corrected

Background: Measurement of myocardial T1 is increasingly incorporated into standard cardiovascular magnetic resonance (CMR) protocols, however accuracy may be reduced in patients with metallic cardiovascular implants. Measurement is feasible in segments free from visual artifact, but there may still be off-resonance induced error. Aim: To quantify off-resonance induced T1 error in patients with metallic cardiovascular implants, and validate a method for error correction for a conventional MOLLI pulse sequence. Methods: Twenty-four patients with cardiac implantable electronic devices (CIEDs: 46% permanent pacemakers, PPMs; 33% implantable loop recorders, ILRs; and 21% implantable cardioverter-defibrillators, ICDs); and 31 patients with aortic valve replacement (AVR) (45% metallic) were studied. Paired mid-myocardial short-axis MOLLI and single breath-hold off-resonance field maps were acquired at 1.5 T. T1 values were measured by AHA segment, and segments with visual artifact were excluded. T1 correction was applied using a published relationship between off-resonance and T1. The accuracy of the correction was assessed in 10 healthy volunteers by measuring T1 before and after external placement of an ICD generator next to the chest to generate off-resonance. Results: T1 values in healthy volunteers with an ICD were underestimated compared to without (967 ± 52 vs. 997 ± 26 ms respectively, p = 0.0001), but were similar after correction (p = 0.57, residual difference 2 ± 27 ms). Artifact was visible in 4 ± 12, 42 ± 31, and 53 ± 27% of AHA segments in patients with ILRs, PPMs, and ICDs, respectively. In segments without artifact, T1 was underestimated by 63 ms (interquartile range: 7–143) per patient. The greatest error for patients with ILRs, PPMs and ICDs were 79, 146, and 191 ms, respectively. The presence of an AVR did not generate T1 error. Conclusion: Even when there is no visual artifact, there is error in T1 in patients with CIEDs, but not AVRs. Off-resonance field map acquisition can detect error in measured T1, and a correction can be applied to quantify T1 MOLLI accurately

Dark blood ischemic LGE segmentation using a deep learning approach

The extent of ischemic scar detected by Cardiac Magnetic Resonance (CMR) with late gadolinium enhancement (LGE) is linked with long-term prognosis, but scar quantification is time-consuming. Deep Learning (DL) approaches appear promising in CMR segmentation. Purpose: To train and apply a deep learning approach to dark blood (DB) CMR-LGE for ischemic scar segmentation, comparing results to 4-Standard Deviation (4-SD) semi-automated method. Methods: We trained and validated a dual neural network infrastructure on a dataset of DB-LGE short-axis stacks, acquired at 1.5T from 33 patients with ischemic scar. The DL architectures were an evolution of the U-Net Convolutional Neural Network (CNN), using data augmentation to increase generalization. The CNNs worked together to identify and segment 1) the myocardium and 2) areas of LGE. The first CNN simultaneously cropped the region of interest (RoI) according to the bounding box of the heart and calculated the area of myocardium. The cropped RoI was then processed by the second CNN, which identified the overall LGE area. The extent of scar was calculated as the ratio of the two areas. For comparison, endo- and epi-cardial borders were manually contoured and scars segmented by a 4-SD technique with a validated software. Results: The two U-Net networks were implemented with two free and open-source software library for machine learning. We performed 5-fold cross-validation over a dataset of 108 and 385 labelled CMR images of the myocardium and scar, respectively. We obtained high performance (&gt; ∼0.85) as measured by the Intersection over Union metric (IoU) on the training sets, in the case of scar segmentation. With regards to heart recognition, the performance was lower (&gt; ∼0.7), although improved (∼ 0.75) by detecting the cardiac area instead of heart boundaries. On the validation set, performances oscillated between 0.8 and 0.85 for scar tissue recognition, and dropped to ∼0.7 for myocardium segmentation. We believe that underrepresented samples and noise might be affecting the overall performances, so that additional data might be beneficial. Figure1: examples of heart segmentation (upper left panel: training; upper right panel: validation) and of scar segmentation (lower left panel: training; lower right panel: validation). Conclusion: Our CNNs show promising results in automatically segmenting LV and quantify ischemic scars on DB-LGE-CMR images. The performances of our method can further improve by expanding the data set used for the training. If implemented in a clinical routine, this process can speed up the CMR analysis process and aid in the clinical decision-making

Can marathon running improve knee damage of middle-aged adults? A prospective cohort study.

Objectives: To evaluate the short-term impact of long-distance running on knee joints using MRI. Methods: 82 healthy adults participating in their first marathon underwent 3T (Tesla) MRI of both knees 6 months before and half a month after the marathon: 71 completed both the 4 month-long standardised training programme and the marathon; and 11 dropped-out during training and did not run the marathon. Two senior musculoskeletal radiologists graded the internal knee structures using validated scoring systems. Participants completed Knee Injury and Osteoarthritis Outcome Score questionnaires at each visit for self-reporting knee function. Results: Premarathon and pretraining MRI showed signs of damage, without symptoms, to several knee structures in the majority of the 82 middle-aged volunteers. However, after the marathon, MRI showed a reduction in the radiological score of damage in: subchondral bone marrow oedema in the condyles of the tibia (p=0.011) and femur (p=0.082). MRI did also show an increase in radiological scores to the following structures: cartilage of the lateral patella (p=0.0005); semimembranosus tendon (p=0.016); iliotibial band (p<0.0001) and the prepatellar bursa (p=0.016). Conclusion: Improvement to damaged subchondral bone of the tibial and femoral condyles was found following the marathon in novice runners, as well as worsening of the patella cartilage although asymptomatic. This is the most robust evidence to link marathon running with knee joint health and provides important information for those seeking to understand the link between long distance running and osteoarthritis of the main weight-bearing areas of the knee

Sex Dimorphism in the Myocardial Response to Aortic Stenosis

OBJECTIVES: The goal of this study was to explore sex differences in myocardial remodeling in aortic stenosis (AS) by using echocardiography, cardiac magnetic resonance (CMR), and biomarkers. BACKGROUND: AS is a disease of both valve and left ventricle (LV). Sex differences in LV remodeling are reported in AS and may play a role in disease phenotyping. METHODS: This study was a prospective assessment of patients awaiting surgical valve replacement for severe AS using echocardiography, the 6-min walking test, biomarkers (high-sensitivity troponin T and N-terminal pro-brain natriuretic peptide), and CMR with late gadolinium enhancement and extracellular volume fraction, which dichotomizes the myocardium into matrix and cell volumes. LV remodeling was categorized into normal geometry, concentric remodeling, concentric hypertrophy, and eccentric hypertrophy. RESULTS: In 168 patients (age 70 ± 10 years, 55% male, indexed aortic valve area 0.40 ± 0.13 cm2/m2, mean gradient 47 ± 4 mm Hg), no sex or age differences in AS severity or functional capacity (6-min walking test) were found. CMR captured sex dimorphism in LV remodeling not apparent by using 2-dimensional echocardiography. Normal geometry (82% female) and concentric remodeling (60% female) dominated in women; concentric hypertrophy (71% male) and eccentric hypertrophy (76% male) dominated in men. Men also had more evidence of LV decompensation (pleural effusions), lower left ventricular ejection fraction (67 ± 16% vs. 74 ± 13%; p < 0.001), and higher levels of N-terminal pro-brain natriuretic peptide (p = 0.04) and high-sensitivity troponin T (p = 0.01). Myocardial fibrosis was higher in men, with higher focal fibrosis (late gadolinium enhancement 16.5 ± 11.2 g vs. 10.5 ± 8.9 g; p < 0.001) and extracellular expansion (matrix volume 28.5 ± 8.8 ml/m2 vs. 21.4 ± 6.3 ml/m2; p < 0.001). CONCLUSIONS: CMR revealed sex differences in associations between AS and myocardial remodeling not evident from echocardiography. Given equal valve severity, the myocardial response to AS seems more maladaptive in men than previously reported. (Regression of Myocardial Fibrosis After Aortic Valve Replacement [RELIEF-AS]; NCT02174471.)

Effective Study: Development and Application of a Question-Driven, Time-Effective Cardiac Magnetic Resonance Scanning Protocol

BACKGROUND: Long scanning times impede cardiac magnetic resonance (CMR) clinical uptake. A “one‐size‐fits‐all” shortened, focused protocol (eg, only function and late‐gadolinium enhancement) reduces scanning time and costs, but provides less information. We developed 2 question‐driven CMR and stress‐CMR protocols, including tailored advanced tissue characterization, and tested their effectiveness in reducing scanning time while retaining the diagnostic performances of standard protocols. METHODS AND RESULTS: Eighty three consecutive patients with cardiomyopathy or ischemic heart disease underwent the tailored CMR. Each scan consisted of standard cines, late‐gadolinium enhancement imaging, native T1‐mapping, and extracellular volume. Fat/edema modules, right ventricle cine, and in‐line quantitative perfusion mapping were performed as clinically required. Workflow was optimized to avoid gaps. Time target was 30% (CMR: from 42±8 to 28±6 minutes; stress‐CMR: from 50±10 to 34±6 minutes, both P45% of cases. Quality grading was similar between the 2 protocols. Tailored protocols did not require additional staff. CONCLUSIONS: Tailored CMR and stress‐CMR protocols including advanced tissue characterization are accurate and time‐effective for cardiomyopathies and ischemic heart diseas

Pulsatile and resistive systolic loads as determinants of left ventricular remodelling after physical training

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): British Heart Foundation Barts Cardiovascular Biomedical Research Centre onbehalf The Marathon Study Consortium Introduction Cardiovascular function depends on the inter-relation between heart and vasculature. The contribution of aorta and peripheral vessels to the total systolic load of the left ventricle (LV) can be represented respectively by a "pulsatile" and a "resistive" component. We sought to understand their interrelation by exploring how LV remodelling occurred with altered load associated with an external stimulus (training). Methods: 237 untrained healthy male and female subjects volunteering for their first-time marathon were recruited. At baseline and after 6 months of unsupervised training, race completers underwent 1.5T cardiac magnetic resonance, brachial and non-invasive central blood pressure assessment. For analysis, runners were divided into 4 groups according to the variation (positive versus null or negative) in Total Arterial Compliance Index (TACi), representing the pulsatile component of the LV load, and in Systemic Vascular Resistance Index (SVRI), representing the resistive component of the LV load. Results: 138runners (age 21-69 years; F: 51%) completed the race. Data are reported for each variable as Δ mean [95% Confidence Interval]. In the whole cohort, training was associated with a small increase in LV mass index (+3g/m2, [0, 6 g/m2]), indexed LV end-diastolic volume (EDVi) (+3ml/m2, [-2, 5 3ml/m2]), in LV mass/LVEDV ratio (+0.02g/ml, [0.00, 0.04 g/ml]) and in TACi (+0.02ml/m2, [0.02, 0.38 ml/m2]). SVRi mildly fell (-43dyn·s/cm2[-103, 17dyn·s/cm2]). TACi increase was associated with LVEDVi increase and no change in LV mass/EDV (eccentric remodelling). On the other hand, both TACi reduction and SVRi increase were associated with increase in LV mass/EDV and no significant change in LVEDVi (concentric remodelling). A similar increase in LV mass was observed in all groups. See Table. Conclusion: Cardiac remodelling observed after mild, medium term, unsupervised training seems to be related to the modifications of aorta and peripheral vessels. In particular, a reduction in pulsatile load seems associated with eccentric LV remodelling, while an increase in both pulsatile and resistive with concentric LV remodelling. Further research is needed to understand the interaction between TACi and SVRi. Table 1 LV EDVi (ml/m2) LV mass index (g/m2) LV mass/EDV TACi increase (n = 75) +4 [0, 9] +3 [0, 7] 0 [-0.03, 0.03] TACi decrease (n = 62) -1 [-6, 4] +3 [0, 8] 0.04 [0.01, 0.07] SVRi increase (n = 63) 0 [-4,4] +3 [0, 7] +0.03 [0, 0.06] SVRi decrease (n = 73) +3 [-3, 7] +3 [-1, 6] +0.01 [-0.02, 0.04